Current indoor surveillance systems mostly rely on contact sensors to monitor states of indoor objects and passive infrared sensors (PIR) to detect the existence of human motions. In some examples, to secure a venue, several sensors need to be deployed and a line-of-sight (LOS) environment is required to detect motions. The existing systems do not learn or update themselves without the help of user feedback. Currently, most home/office security systems consist of a control panel, contact sensors, and PIRs. The contact sensors are devices using magnetism or electric currents to detect if the contact is established or broken and have been widely installed on doors and windows to monitor their open and close activities. PIR sensors detect moving objects that can generate heat in the environment by tracking the changes in the received infrared waves. In some examples, each of the sensors has limited coverage of monitoring in that the contact sensors need to be attached on the doors and the PIR sensors require line-of-sight to detect moving objects. Moreover, the cost increases significantly when more events are to be detected when protecting the venue.
Recently, sensing with wireless signals to detect indoor events and activities has gained much attention. Because received radio frequency (RF) signals can be altered by the propagation environment, device-free indoor sensing systems are capable of monitoring activities in the environment through the changes in received RF signals. Examples of features of RF signals that can be used to identify variations during signal transmission for indoor events detection include the received signal strength (RSS) and channel state information (CSI). Due to its susceptibility to environmental changes, the RSS indicator (RSSI) can be applied to indicate and further recognize indoor activities. Channel state information is now accessible in some commercial devices.
Another category of technologies in device-free indoor monitor systems is adopted from radar technology to track targets using their reflections. The radar technique can identify the delays of sub-nanoseconds in the time-of-flight (ToF) of wireless signals through different paths, by using ultra-wideband (UWB) sensing.
However, the technologies mentioned above for indoor monitor systems have limitations. First, the resolution of received signal strength indicator for differentiating between different indoor events and objects is low because the received signal strength indicator as a scalar has only a single degree of freedom and is severely affected by multipath effects. In the received signal strength indicator-based systems, the performance of indoor detection is guaranteed at the cost of deploying multiple sensing devices or antennas. Moreover, most channel state information-based indoor sensing systems only rely on the amplitudes of the channel state information, whereas the phase information is discarded regardless of how informative it is. On the other hand, in order to acquire different ToF information the radar-based techniques consume over 1 GHz bandwidth to sense the environment that cannot be realized through commercial WiFi devices, and the result obtained from the sensors often require further effort to detect the type of the indoor events.